舰艇自噪声自适应有源抵消技术研究
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摘要
随着社会的发展,无论民用领域还是军事领域,噪声控制问题正越来越受到重视。噪声控制技术也取得了长足进步,但是仍有许多问题有待解决。信号存在情况下的有源噪声控制(ANC)技术就是一个新近被提出的重要问题。
本文着重进行了以下几个方面的研究:信号存在情况下的“具有信噪比提升能力的ANC技术”理论研究;为了解决降噪和信号失真问题,进行的新型算法和结构研究;实际声场中常见的信道在线建模问题研究;以及工程应用将要面临的互耦合多通道系统研究。
传统ANC系统的待抵消噪声中不包含有用信号,噪声希望被完全抵消;但在某些特殊的应用场合里,特别是对引入新的声场极度敏感的舰艇环境,待抵消噪声(主要是舰艇自噪声)中包含有信号(目标信号),噪声被降低的同时,信号希望被保留,这就是“具有信噪比提升能力的ANC系统”。本文构建了这种系统的物理模型,分析了针对该系统的“噪声处理增益(这里特指降噪能力)”、“系统处理增益(这里特指信噪比提升能力)”、“信号失真度”和“信号失真测度”概念,完善了理论体系,完成了仿真实验。研究表明:该类系统能够降低噪声,但是信号会失真,影响该系统性能的最主要因素是参考输入端信噪比的大小。也就是说,只要合理设计参考噪声的拾取方式,该系统能够用于抵消干扰噪声,在获得较高的系统增益同时,保持较低的信号失真程度。
根据上述理论,本文提出了几种新型系统用于解决降噪和信号失真问题。这些系统包括:利用独立成份分析方法对参考输入进行预处理的ANC系统,以及利用抗串扰自适应抵消器对参考输入进行预处理的ANC系统。完成了理论分析、仿真实验和海试数据的处理,其结果表明:这些预处理技术降低了信号和噪声之间的干扰,根据“具有信噪比提升能力的ANC系统”性能评价指标体系,这些新型系统具有现有系统所没有的优良性能。针对现有的时域、频域和小波分解ANC系统不具备任意的时间、频率(高频细节和低频轮廓)分辨能力的弊端,本文提出了基于小波包分解的ANC系统,推导了滤波-X(FX)结构下的LMS算法和RLS算法。完成了理论分析、仿真实验和海试数据的处理,结果表明该系统具有先天的技术优势和现有系统所不具备的良好性能。
真实声信道的存在是ANC技术和自适应降噪技术的本质区别之一。本文对信道在线建模ANC技术进行了深入的研究,指出了现有技术存在的问题:建模和控制之间相互干扰,以及次级信道对用于建模的激励源的响应增大了系统收敛后的声场能量。本文提出了三种新的信道在线建模ANC系统:改进型FX结构次级通道在线建模ANC系统、基于峰值预滤波的次级通道在线建模ANC系统、以及考虑参考输入信道的同步方程ANC系统。理论分析、仿真实验和海试数据处理结果表明:这些系统各具优势,在一定程度上能够较好地解决上述两个问题。
多通道ANC系统是区域降噪的必然之选,本文对多通道“耦合”问题进行了研究。并且以单通道改进型FX结构ANC系统为例,对其进行了多通道推广,给出了多通道FXRLS算法表达式,完成了理论分析和计算机仿真实验。结果表明该多通道系统具有良好的降噪性能。
With the development of society, the subjects of noise control have attracted more and more attention in both civil and military fields. Great progresses have been made up till now, however there are still many problems remaining to be solved. The technique of active noise control (ANC) in the presence of useful signals is just an important subject which arises recently.
In this dissertation, some aspects of the subject have been studied: theories of new ANC technique with SNR (Signal-to-Noise Ratio) processing gain in the environments of noise and signals; algorithms and systems for noise cancellation while retaining signals undisturbed; methods of online path modeling encountered in real sound field; and cross-coupled multi-channel ANC systems for practical applications and acoustic simulation experiments.
The noise is always hoped to be cancelled completely in the conventional ANC system because it does not have any useful information in most cases. But in some special application environments, such as the naval ships where it is extremely sensitive to newly introduced sound field, and the noise to be cancelled (mostly, the ship's self-noise) contains useful signals (target signals). The ANC system is expected to have the highest level of noise reduction while to retain the signal energy in the greatest extent. This kind of system is defined as ANC system with SNR processing gain. In the dissertation, the system physical model was built; concepts of "noise processing gain", "SNR processing gain", "signal distortion" and "signal distortion measurement" for the system were introduced and mathematically defined; a relatively complete theoretical system was established; and the computer simulation tests had been conducted as well. The results show that the newly developed system based on classical ANC principles works but the signal will be distorted in some degree, and the most important factor that influences the system performance is the SNR of reference input. In other words, if the reference input is designed to be picked up the properly, the system can used to cancel the interference noise, obtaining great SNR processing gain while retaining a low level signal distortion.
Based on the above theories, several novel systems are proposed to solve the problems concerning noise cancellation and signal distortion. These systems include two kinds of ANC systems with pretreated reference input using independent component analysis (ICA) in time and frequency domains, respectively and an ANC system with pretreated reference input using crosstalk resistant adaptive noise canceller (CRANC). Theoretical analysis, computer simulation tests and processing of raw data collected from sea run tests are accomplished. The results show that these preprocessing techniques can reduce the cross interferences between signal and noise. Examined by the performance indexes of the ANC system with SNR processing gain, these new systems have better capabilities than existing systems.
Aiming at the lacking capability of optional time and frequency (high frequency details and low frequency contour) resolution for existing time domain, frequency domain and wavelet decomposing domain ANC systems, a new system structure is proposed to solve this problem. This dissertation proposed a new filtered-X (FX) ANC system based on wavelet packet decomposing (WPD). LMS and RLS algorithms are derived under the filtered-X (FX) structure. Theoretical analysis, computer simulation tests and processing of real data collected from sea run tests are accomplished. Results show that the proposed scheme has inherent technical advantages and favorable performances which the conventional ANC system does not have.
The existing of real sound path is one of the essential differences between ANC and adaptive noise cancellation. The online path modeling technique of ANC system has been studied intensively in this dissertation. Disadvantages of current techniques are that there exists disturbance between modeling filter and control filter, and that the exciting source for online secondary path modeling will increase the energy of sound field after system convergence Three new online path modeling ANC systems are proposed in this dissertation: modified FX structure online secondary path modeling ANC system, online secondary path modeling ANC system based on peak prefiltering technique, and ANC system of simultaneous equations which considers the existing of reference input path. The theoretic analysis, computer simulation tests and processing of real data collected from sea run tests are carried out. The results show that these systems have advantages on their own, and can be used to solve the two problems mentioned above in a certain extent.
Multi-channel ANC system is the inevitable choice for regional noise cancellation. The problem of cross-couple of multi-channel has been studied in this dissertation. As an example, the modified FX structure is generalized into multi-channel ANC system. Algorithm of multi-channel FXRLS is developed. Theoretical analysis and computer simulation tests show that the multi-channel ANC system has good capabilities.
本文着重进行了以下几个方面的研究:信号存在情况下的“具有信噪比提升能力的ANC技术”理论研究;为了解决降噪和信号失真问题,进行的新型算法和结构研究;实际声场中常见的信道在线建模问题研究;以及工程应用将要面临的互耦合多通道系统研究。
传统ANC系统的待抵消噪声中不包含有用信号,噪声希望被完全抵消;但在某些特殊的应用场合里,特别是对引入新的声场极度敏感的舰艇环境,待抵消噪声(主要是舰艇自噪声)中包含有信号(目标信号),噪声被降低的同时,信号希望被保留,这就是“具有信噪比提升能力的ANC系统”。本文构建了这种系统的物理模型,分析了针对该系统的“噪声处理增益(这里特指降噪能力)”、“系统处理增益(这里特指信噪比提升能力)”、“信号失真度”和“信号失真测度”概念,完善了理论体系,完成了仿真实验。研究表明:该类系统能够降低噪声,但是信号会失真,影响该系统性能的最主要因素是参考输入端信噪比的大小。也就是说,只要合理设计参考噪声的拾取方式,该系统能够用于抵消干扰噪声,在获得较高的系统增益同时,保持较低的信号失真程度。
根据上述理论,本文提出了几种新型系统用于解决降噪和信号失真问题。这些系统包括:利用独立成份分析方法对参考输入进行预处理的ANC系统,以及利用抗串扰自适应抵消器对参考输入进行预处理的ANC系统。完成了理论分析、仿真实验和海试数据的处理,其结果表明:这些预处理技术降低了信号和噪声之间的干扰,根据“具有信噪比提升能力的ANC系统”性能评价指标体系,这些新型系统具有现有系统所没有的优良性能。针对现有的时域、频域和小波分解ANC系统不具备任意的时间、频率(高频细节和低频轮廓)分辨能力的弊端,本文提出了基于小波包分解的ANC系统,推导了滤波-X(FX)结构下的LMS算法和RLS算法。完成了理论分析、仿真实验和海试数据的处理,结果表明该系统具有先天的技术优势和现有系统所不具备的良好性能。
真实声信道的存在是ANC技术和自适应降噪技术的本质区别之一。本文对信道在线建模ANC技术进行了深入的研究,指出了现有技术存在的问题:建模和控制之间相互干扰,以及次级信道对用于建模的激励源的响应增大了系统收敛后的声场能量。本文提出了三种新的信道在线建模ANC系统:改进型FX结构次级通道在线建模ANC系统、基于峰值预滤波的次级通道在线建模ANC系统、以及考虑参考输入信道的同步方程ANC系统。理论分析、仿真实验和海试数据处理结果表明:这些系统各具优势,在一定程度上能够较好地解决上述两个问题。
多通道ANC系统是区域降噪的必然之选,本文对多通道“耦合”问题进行了研究。并且以单通道改进型FX结构ANC系统为例,对其进行了多通道推广,给出了多通道FXRLS算法表达式,完成了理论分析和计算机仿真实验。结果表明该多通道系统具有良好的降噪性能。
With the development of society, the subjects of noise control have attracted more and more attention in both civil and military fields. Great progresses have been made up till now, however there are still many problems remaining to be solved. The technique of active noise control (ANC) in the presence of useful signals is just an important subject which arises recently.
In this dissertation, some aspects of the subject have been studied: theories of new ANC technique with SNR (Signal-to-Noise Ratio) processing gain in the environments of noise and signals; algorithms and systems for noise cancellation while retaining signals undisturbed; methods of online path modeling encountered in real sound field; and cross-coupled multi-channel ANC systems for practical applications and acoustic simulation experiments.
The noise is always hoped to be cancelled completely in the conventional ANC system because it does not have any useful information in most cases. But in some special application environments, such as the naval ships where it is extremely sensitive to newly introduced sound field, and the noise to be cancelled (mostly, the ship's self-noise) contains useful signals (target signals). The ANC system is expected to have the highest level of noise reduction while to retain the signal energy in the greatest extent. This kind of system is defined as ANC system with SNR processing gain. In the dissertation, the system physical model was built; concepts of "noise processing gain", "SNR processing gain", "signal distortion" and "signal distortion measurement" for the system were introduced and mathematically defined; a relatively complete theoretical system was established; and the computer simulation tests had been conducted as well. The results show that the newly developed system based on classical ANC principles works but the signal will be distorted in some degree, and the most important factor that influences the system performance is the SNR of reference input. In other words, if the reference input is designed to be picked up the properly, the system can used to cancel the interference noise, obtaining great SNR processing gain while retaining a low level signal distortion.
Based on the above theories, several novel systems are proposed to solve the problems concerning noise cancellation and signal distortion. These systems include two kinds of ANC systems with pretreated reference input using independent component analysis (ICA) in time and frequency domains, respectively and an ANC system with pretreated reference input using crosstalk resistant adaptive noise canceller (CRANC). Theoretical analysis, computer simulation tests and processing of raw data collected from sea run tests are accomplished. The results show that these preprocessing techniques can reduce the cross interferences between signal and noise. Examined by the performance indexes of the ANC system with SNR processing gain, these new systems have better capabilities than existing systems.
Aiming at the lacking capability of optional time and frequency (high frequency details and low frequency contour) resolution for existing time domain, frequency domain and wavelet decomposing domain ANC systems, a new system structure is proposed to solve this problem. This dissertation proposed a new filtered-X (FX) ANC system based on wavelet packet decomposing (WPD). LMS and RLS algorithms are derived under the filtered-X (FX) structure. Theoretical analysis, computer simulation tests and processing of real data collected from sea run tests are accomplished. Results show that the proposed scheme has inherent technical advantages and favorable performances which the conventional ANC system does not have.
The existing of real sound path is one of the essential differences between ANC and adaptive noise cancellation. The online path modeling technique of ANC system has been studied intensively in this dissertation. Disadvantages of current techniques are that there exists disturbance between modeling filter and control filter, and that the exciting source for online secondary path modeling will increase the energy of sound field after system convergence Three new online path modeling ANC systems are proposed in this dissertation: modified FX structure online secondary path modeling ANC system, online secondary path modeling ANC system based on peak prefiltering technique, and ANC system of simultaneous equations which considers the existing of reference input path. The theoretic analysis, computer simulation tests and processing of real data collected from sea run tests are carried out. The results show that these systems have advantages on their own, and can be used to solve the two problems mentioned above in a certain extent.
Multi-channel ANC system is the inevitable choice for regional noise cancellation. The problem of cross-couple of multi-channel has been studied in this dissertation. As an example, the modified FX structure is generalized into multi-channel ANC system. Algorithm of multi-channel FXRLS is developed. Theoretical analysis and computer simulation tests show that the multi-channel ANC system has good capabilities.
引文
[1]Robert J.Urick.水声原理。洪申译.第三版.哈尔滨:哈尔滨船舶工程学院出版社,1990:279-280页
[2]陈克安.有源噪声控制.北京:国防工业出版社,2003:1-9页
[3]Lueg P.Process of silencing sound oscillations,German patent DRP No.644408,1933
[4]Lueg P.Process of silencing sound oscillations,US patent No.2043416,1936
[5]Widrow B,Glover J R,McCool J M.Adaptive noise cancellation:principle and applications,Proceeding of IEEE.1975,63(12):1692-1716P
[6]Burgress J.C.Active adaptive sound control in a duct:a computer simulation.Journal of the Acoustical Society of America.1981:70(3),714-726P
[7]S.J.Elliott,I.M.Stothers,P.A.Nelson,A.M.McDonald,D.C.Quinn,T.Saunders.The active control of engine noise inside cars,Proc.Inter-noise.1988:987-990P
[8]A.M.McDonald,S.J.Elliott,M.A.Stokes.Active noise and vibration control within the automobile,Proc.Int.Symp.Active control of Sound Vibration.1991:147-156P
[9]Y.Kurata,N.Koike.Adaptive active attenuation of interior car noise,Proc.Int.Symp.Active control of Sound Vibration.1991:297-302P
[10]C.F.Ross.the control of noise inside passenger vehicles,Proc.Recent Advances in Active control of Sound Vibration.1991:671-681P
[11]S.M.Kuo,B.M.Finn.A general multi-channel filtered LMS algorithm for 3-D active noise control systems.Proc.2nd Int.Conf.Recent development in Air- and Structure- Borne Sound Vib.1992:345-352P
[12]M.A.Simpson,T.M.Luong,M.A.Swinbanks,M.A.Russell,H.G.Leventhall,Full scale demonstration tests of cabin noise reduction using active nose control.Proc.Inter-noise.1989:459-462P
[13]C.M.Dorling,G.P.Eatwell,S.M.Hutchins,C.F.Ross,S.G.C.Sutcliffe.A demonstration of active noise reduction in an aircraft cabin.J.Sound Vibration.1989:128(2):358-360P
[14]S.J.Elliott,P.A.Nelson,I.M.Stotheers,C.C.Boucher.In-flight experiments on the active control of propeller-induced cabin noise.J.Sound Vibration.1990,140(2):219-238P
[15]J.-D.WU,M.R.BAI.Application of feedforward adaptive active-noise control for reducing blade passing noise in centrifugal fans.Journal of Sound and Vibration.2001,239(5):1051-1062P
[16]JamesP.Carneal,ChrisR.Fuller.An analytical and experimental investigation of active structural acoustic control of noise transmission through double panel systems.Journal of Sound and Vibration.2004,272:749-771P
[17]Yuan It.Guan,Teik C.Lim,W.Steve Shepard,Jr.Experimental study on active vibration control of a gearbox system.Journal of Sound and Vibration.2005,282:713-733 P
[18]Desheng Li.Active control of aircraft cabin noise and vibration using a physical model:[PhD dissertation].Université Laval,Québec Canada.2002,12.
[19]美国在C-130H飞机的座舱中安装ANC主动噪声控制系统.现代兵器.2004,(5):46页
[20]LAU,Siu Kit.Active control of sound transmission into enclosure through a panel:[PhD dissertation].Hong Kong Polytechnic University.2002,12.
[21]Theeraphong Chanpheng,Hitoshi Yamada,Toshio Miyata,Hiroshi Katsuchi.Application of radiation modes to the problem of low-frequency noise from a highway bridge.Applied Acoustics,2004,65:109-123P
[22]陈克安,马远良.自适应有源噪声控制--原理、算法及实现.西安:西北工业大学出版社,1993:280页
[23]D.H.Crawford and R.W.Stewart,E.Toma.A novel adaptive IIR filter for active noise control. Proceeding of the IEEE, 1996:1629-1632P
[24] Scott D.Snyder. Active control using IIR filters- a second look. Proceeding of the IEEE, 1994:241-244P
[25] Jong Boo Kim, Tae Pyo Lee, Kook Hyun Yim. Feedforward IIR active noise control using genetic algorithm. Proceeding of the IEEE, 1999:436-441P
[26] Carlos Mosquera, Jose A, Gomez and Fernando Perez-Gonzalez. Filtered error adaptive algorithms and their application to active noise control.Proceeding of the IEEE, 1998:1701-1704P
[27] Kook Hyun Yim, Jong Boo Kim, Tae Pyo Lee, Doo Soo Ahn. Genetic adaptive IIR filtering algorithm for active noise control. Proceedings of IEEE International Fuzzy Systems Conference, 1999:1723-1728P
[28] Akhtar, M.T.; Abe, M.; Kawamata, M.; A new method for active noise control systems with online acoustic-feedback-path modeling. IEEE International Conference on Engineering of Intelligent Systems 22-23 April 2006:1-6P
[29] Martin Bouchard. Numerically stable fast convergence least-squares algorithms for multichannel active sound cancellation systems and sound deconvolution systems. Signal Processing. 2002:721-736P
[30] Martin Bouchard, Stephan Quednau. Multichannel recursive-least-squares algorithms and fast-transversal-filter algorithm for active noise control and sound reproduction systems. IEEE Trans. Acoustics, Speech and Signal Processing,2000,8(5): 606-618P
[31] Young C. Park, Scott D. Sommerfeldt. A fast adaptive noise control algorithm based on the lattice structure. Applied Acoustics. 1996,47:1-25P
[32] Kensaku Fujii, Juro Ohga. Method to update the coefficients of the secondary path filter under active noise control. Signal Processing.2001,81:381-387P
[33] X.Qiu, C.H.Hansen. An algorithm for active control of transformer noise with on-line cancellation path modelling based on the perturbation method. Journal of Sound and Vibration. 2001,240(4):647-665P
[34] Alberto Gonzalez, Jose J.Lopez. Time domain recursive deconvolution in sound reproduction. IEEE, 2000:833-835P
[35] H.-S. Kim, Y.Park. Delayed-X LMS algorithm: an efficient ANC algorithm utilizing robustness of cancellation path model. Journal of Sound and Vibration. 1998, 212(5):875-887P
[36] D.C.Swanson, S.M.Hirsch, K.M.Reichard, J.Tichy. Development of a frequency-domain filtered-x intensity ANC algorithm. Applied Acoustics,1999:39-49P
[37] Cheng-Yuan Chang and Kuo-Kai Shyu. A self-tuning fuzzy filtered-U algorithm with the application of active noise control. The 27th Annual Conference of the IEEE Industrial Electronics Society. 2001:474-478P
[38] Sven Johansson, Sven Nordebo, Ingvar Claesson. Convergence analysis of a twin-reference complex least-mean-squares algorithm. IEEE Trans. on Speech and Audio Processing.2002:213-221P
[39] A. Kuo Wang, Wei Ren. Convergence analysis of the filtered-U algorithm for active noise control. Signal Processing. 1999.73:255-266P
[40] Martin Bouchard. Inverse structure for active noise control and combined active noise control/sound reproduction systems. IEEE Trans. Speech and Audio Processing. 2001,9(2):141-151P
[41] Masato Miyoshi, Yutaka Kaneda. Inverse filtering of room acoustics. IEEE Trans. on Acoustics, Speech, and Signal Processing. 1988, 36(2):145-152P
[42] Martin bouchard. New recursive-least-squares algorithms for nonlinear active control of sound and vibration using neural networks. IEEE Trans. on Neural Networks.2001,12(1):135-147P
[43] Li Tan, Jean Jiang. Adaptive volterra filters for active control of nonlinear noise processes. IEEE Trans. on Signal Processing.2001,49(8): 1667-1676P
[44] Debi Prasad Das, Ganapati Panda. Active mitigation of nonlinear noise processes using a novel filtered-s LMS algorithm. IEEE Trans. On Speech and Audio Processing. 2004, 12(3):313-322P
[45]Ya-Li Zhou,Qi-Zhi Zhang,Xiao-Dong Li,Woon-Seng Gao.Analysis and DSP implementation of an ANC system using a filtered-error neural network.Journal of Sound and Vibration.2005,285:1-25P
[46]K.Mayyas,T.Aboulnasr.A fast exact weighted subband adaptive algorithm and its application to mono and stereo acoustic echo cancellation.Journal of the Franklin Institute.2005,342:235-253P
[47]Bernhard H.Nitsch.A frequency-selective stepfactor control for an adaptive filter algorithm working in the frequency domain.Signal Processing.2000,80:1733-1745P
[48]孙利峰,陈克安,谢达.多通道有源控制算法硬件实现及影响因素研究.电声技术.2007,31(2):63-66页
[49]陈克安,陈国跃,李双,潘浩然.分布式位移传感下的有源声学结构误差传感策略.声学学报.2007,32(1):42-48页
[50]李双,陈克安.有源声学结构次级声源的布放规律研究.机械科学与技术.2006,2(11):1351-1357页
[51]陈克安,尹雪飞.应用于多通道有源控制的自适应组合逆算法.信号处理.2006,22(3):366-369页
[52]张玉麟.小波自适应控制系统及其在噪声主动控制中的应用研究.重庆大学博士学位论文.2002:4页
[53]张玉麟,陈伟民,黄尚廉.噪声主动控制中的自适应算法和传函识别研究.中国机械工程.2002,13(1):46-49页
[54]张玉麟,陈伟民,黄尚廉,小波变换自适应滤波器及在噪声主动控制中的应用.控制与决策.2002,17(1):107-110页
[55]孙旭,陈端石.基于无限脉冲响应滤波器的自适应滤波E型有源噪声控制算法.声学学报.2003,28(2):171-176页
[56]孙旭,陈端石.次级通道模型误差下滤波X型最小均方差算法性能的分析.声学学报.2003,28(1):73-78页
[57]于华民,朱海潮,施引.管道复合主动噪声控制系统及其实现.振动、测试与诊断.2004,24(2):153-156页
[58]王登峰,刘学广,刘宗巍,梁杰.基于发动机转速的车内有源控制策略和 自适应算法.公路交通科技.2004,21(10):126-129页
[59]常振臣,王登峰.车內噪声控制技术研究现状及展望.吉林大学学报(工学版).2002,32(4):86-90页
[60]常振臣,王登峰.车内噪声主动控制系统设计与实验研究.公路交通科技.2003,20(6):150-153页
[61]LI Keqiang,YANG Diange,ZHENG Sifa,LIAN Xiaomin,Tanaka Takeharu.Active Noise Control for Vehicle Exhaust Noise Reduction.清华大学学报(自然科学英文版).2003,8(5):577-581页
[62]吴亚锋,黎中伟,任辉.应用于主动噪声控制的实时DSP系统.振动与冲击.2002,21(2):91-93页
[63]吴亚锋,任辉,李江红.螺桨飞机舱内噪声的主动控制.声学技术.2001,20(1):29-31页
[64]吴亚锋.三维闭空间主动噪声控制的实验研究.振动与冲击.2001,20(4):33-35页
[65]任辉,黎中伟.主动噪声控制声学通道的实验辨识.应用声学.1997,16(3):36-40页
[66]黎中伟代杏珍.螺浆飞机舱内主动噪声控制地面实验.西北工业大学学报.1996,14(4):651-653页
[67]胡啸,涂有.超机动车车室内复合主动噪声控制系统的设计.噪声与振动控制.2001,21(1):8-12页
[68]李传光,姜丽飞,李长青.RB网络在履带车辆舱室内有源降噪的实验研究.北京理工大学学报.2004,24(4):297-299页
[69]李传光,车星峰,韩秀苓.局部空间自适应有源降噪系统的实验研究.北京理工大学学报.2001,21(4):495-497页
[70]王杰.互耦多通道自适应有源噪声抵消技术研究.哈尔滨工程大学博士学位论文.2004:4页
[71]王杰,徐新盛,吴英姿.一种采用脉冲串的自适应有源干扰抵消器.应用声学.2004,23(6):45-50页
[72]王杰,徐新盛,刘清宇,吴英姿.一种用于宽带自噪声有源抵消的无延时子带多通道系统.噪声与振动控制.2004,24(4):5-7页,25页
[73]王杰,徐新盛,吴英姿.自噪声有源抵消器性能分析.海洋技术.2004,23(3):26-29页,33页
[74]张奇志,贾永乐.噪声有源稳定自适应控制.振动工程学报.2002,15(1):86-89页
[75]尹建民,周雅莉,张奇志,关碧华.有源噪声控制的一种变换域算法.应用声学.2004,23(3):33-39页
[76]张奇志,贾永乐.噪声有源控制的递归神经网络方法.控制与决策.2001,16(3):368-370页
[77]张志涛,张奇志.无模型技术在有源噪声控制中的应用.电声技术.2004,10:51-53页
[78]熊斌,张奇志,周雅莉,吕小明.内模型神经网络在有源噪声控制中的应用.电声技术.2005,11:58-60页
[79]朱晓健,韩彦民,张懿时,刘宝,徐琳琳.智能调频消声器的设计和实现.噪声与振动控制.2006,26(5):85-87页
[80]关碧华,周雅莉.噪声有源控制的模糊神经网络方法.北京机械工业学院学报.2002,17(3):11-14页
[81]李径定,罗永革.汽车车内结构噪声新型控制方法实验研究.汽车工程.2001,23(4):262-265页
[82]张菊香,邱阳.基于自调整量化因子模糊控制器的有源噪声控制.噪声与振动控制.2002,22(6):13-15页
[83]Simon Haykin.Adaptive filter theory.Fourth Edition.Beijing:Publishing House of Electronics Industry,2002:94-128P
[84]Widrow B,Stearns S D.Adaptive signal processing,Prentice-Hall,Englewood Cliffs,NJ,1985
[85]B.Widrow,E.Walach.自适应逆控制.刘树荣,韩崇昭译.西安:西安交通大学出版社,2000:52-59页
[86]Min-Chun Pan;Ji-Yao Liu;Active shock noise cancellation with variable step-size algorithms.Information Acquisition,2005 IEEE International Conference on 27 June-3 July 2005:198-203P
[87]Yue Wang;Chun Zhang;Zhihua Wang.A new variable step size LMS algorithm with application to active noise control.Acoustics,Speech,and Signal Processing,2003.Proceedings.(ICASSP '03).2003 IEEE International Conference.2003,5:573-575P
[88]Say-Wei Foo;Senthilkumar,T.N.;Averty,C.;Active noise cancellation headset.Circuits and Systems,2005.ISCAS 2005.IEEE International Symposium,23-26 May.2005,1:268-271P
[89]沙家正,孙广荣,曹水轩,吴启学.有源消声的机理研究.声学学报.1983,8(2):93-99页
[90]田静.关于单极子次级声源管道降噪能量机制的理论分析.声学学报.1992,17(5):369-374页
[91]Synder S D,Hansen C H.Active noise control in duct:Some physical insights.Journal of the Acoustical of America.1989,86:184-194P
[92]Elliott S J,Nelson P A,Johnson M E.Power output minimization and power absorption in the active control of sound.Journal of the Acoustical Society of America.1993,94:185-195P
[93]沙正明,沙家正,单扬声器的管道有源消声器.声学学报.1987,15(3):343-348页
[94]Warnaka G E,Poole L A,Tichy J.Active acoustic attenuators,U.S.Patent 4473906,1984
[95]Eriksson L J.Development of the filtered-U algorithm for active noise control,Journal of the Acoustical Society of America.1991,89(1):257-265P
[96]Burgress J C.Active adaptive sound control in a duct:a computer simulation,Journal of the Acoustical Society of America.1981,70(3):715-726P
[97]Bjarmason E.Analysis of the filtered-X LMS algorithm,IEEE Trans.On Speech and Audio Processing.1995,3:504-514P
[98]Feintuch P L,Bershad N J,Lo A K.A frequency domain model for "filtered" LMS algorithms - stability analysis,design,and elimination of the training mode,IEEE Trans.On Signal Processing.1993,41(4):1518-1531P
[99]陈克安,马远良.自适应宽带有源消声.声学学报.1994,19(2):101-109页
[100]Radoslav Bortel,Pavel Sovka.EEG-EMG coherence enhancement.Signal Processing.2006,86:1737-1741P
[101]Sen M.Kuo,Dennis R.Morgan.Active noise control:a tutorial review.Proceedings of the IEEE.1999,87(6):943-973P
[102]Eriksson L J,Allie M C.Allie.Use of random noise for on-line transducer modeling in an adaptive active attenuation system.Journal of the Acoustical Society of America.1989,85:797-802P
[103]Rufus Fraanje,Michel Verhaegen,Nick Doelman.Convergence analysis of the Filtered-U LMS algorithm for active noise control in case perfect cancellation is not possible.Signal Processing.2003,83:1239-1244P
[104]S.M.Kuo,D.R.Morgan.Active Noise Control Systems:Algorithm and DSP Implementations.New York:Wiley.1996.
[105]M.Ayala Botto,J.M.C.Sousa da Costa,J.M.G.Sá.Intelligent active noise control applied to a laboratory railway coach model.Control Engineering Practice.2004,13:473-484P
[106]Jing Yuan.A hybrid active noise controller for finite ducts.Applied Acoustics.2004,64:44-47P
[107]Jun-il Sohn,Minho Lee.Selective attention system using new active noise controller.Neurocomputing.2000,31:197-204P
[108]刘伯胜,雷加煜.水声学原理.哈尔滨:哈尔滨工程大学出版社,1997:159-183页,213-236页
[109]沙家正.管道有源消声器.声学学报.1982,7(2):137-147页
[110]Swinbanks M A.The active control of sound propagation in long ducts.Journal of Sound and Vibration.1973:411-436P
[111]谷萩隆嗣.语音与图像的数字信号处理.朱虹译.北京:科学出版社,2003:11-17页
[112]Itoh Y.,Tajima K.,Kuwabara N..Measurement of subjective communication quality for optical mobile communication systems by using mean opinion score.Personal,Indoor and Mobile Radio Communications,2000.PIMRC 2000.The 11th IEEE International Symposium on,2000,2:1330-1334P
[113]Andres Buzo,Federico Kuhlmann,Carlos Rivera.Rate-distortion bounds for quotient-based distortions with application to Itakura-Saito distortion measures.IEEE transactions on information theory.1986,32(2):141-147P
[114]Hermansky H.Perceptual Linear Predictive(PLP) Analysis of Speech.The Journal of the Acoustical Society of America.1990,87(4):1738-1752P
[115]易克初,田斌,付强.语音信号处理.北京:国防工业出版社,2000:331-339页,135-148页
[116]Wonho Yang,Benbouchta,M.,Yantorno,R..Performance of the modified Bark spectraldistortion as an objective speech quality measure.Acoustics,Speech,and Signal Processing,1998.ICASSP '98.Proceedings of the 1998IEEE International Conference on,Seattle,WA,USA.1998,1:541-544P
[117]Wonho Yang,Yantorno R.Improvement of MBSD by scaling noise masking threshold and correlation analysis with MOS difference instead of MOS.Acoustics,Speech,and Signal Processing,1999.ICASSP '99.Proceedings of the 1999 IEEE International Conference on,Phoenix,AZ,USA,1999,2:673-676P
[118]P.Comon.Independent component analysis-a new concept.Signal Processing.1994,36:287-314P
[119]Delfosse,N.,Loubaton,P.Adaptive blind separation of independent sources:A deflation approach.Signal Processing.1995,45:59-83P
[120]Ye Jimin,Zhang Xianda,Zhu Xiaolong.Blind source separation with unknown and dynamicall changing number of source Signals.Science in China Series F:Information Sciences.2006,49(5):627-638P
[121]徐尚志,苏勇,叶中付.欠定条件下的盲分离算法.数据采集与处理,2006,21(2):128-132页
[122]M.Joho,H.Mathis,R.H.Lambert,Overdetermined blind source separation:using more sensors than source signals in a noisy mixture,Proceedings of International Conference on Independent Component Analysis and Blind Signal Separation(ICA).Helsinki,Finland,June 19-22,2000:81-86P
[123]J.S(a|¨)rel(a|¨),H.Valpola.Denoising source separation.Journal of Machine Learning Research.2005,6:233-272P
[124]梅铁民.盲源信号分离时域与频域算法研究.大连理工大学博士学位论文.2005:28-134页
[125]C.Jutten,J.Karhunen.Advances in blind source separation(BSS) and independent component analysis(ICA) for nonlinear mixtures.Int.J.of Neural Systems.2004,14(5):267-292,2004P
[126]Su Yong,Xu Shangzhi,Ye Zhongfu.Blind channel identication of nonlinear folding mixing model.Journal of Systems Engineering and Electronics.2006,17(3):509-512P
[127]Aapo Hyv(a|¨)inen,Erkki Oja,Independent component analysis:algorithms and applications.Neural Networks.2000,13(4-5):411-430P
[128]Hyv(a|¨)inen,E.Oja,A fast fixed-point algorithm for independent component analysis.Neural Computation.1997,9:1483-1492P
[129]Bell A.J.,Sejnowski T.J.Edges are the independent components of natural scenes.Advances in Neural Information Processing Systems 9.MIT press.1996.
[130]Lee T W Bell A J,Lambert Blind separation ofdelayed and convolved sources,in Advances in Neural Information Processing Systems 9.Combridge,MA:MIT Press,1997:758-764P
[131]Ikeda S,Murata N.A method of ICA in time-frequency domain,in Int.Conf.ICA and Signal Separation Aussois,France.1999:365-371P
[132]Bell A.J.,Sejnowsld T.J.An information maximization approach to blind separation and blind deconvolution.Neural Computation,1995,7(6):1129-1159P
[133]Smaragdis P.Blind separation of convolved mixtures in the frequency domain.Neurocomputing.1998,22(6):21-34P
[134]Parra L,Spence C.Convolutive blind separation of non-stationary sources.IEEE Trans.Speech Audio Processing.2000,8(3):320-327P
[135]Asano E Ikeda S,Ogawa M,Asoh H,Kitawaki N.Combined approach of array processing and independence component analysis for blind separation of acoustic signals. IEEE trans. Speech, Audio Processing.2003,11(5):204-215P
[136] Murata N, Ikeda S, Ziehe A. An approach to blind source separation based on temporal structure of speech signals. Neurocomput. 2001,41(2):1-24P
[137] Matsuoka K. Independent component analysis and its applications to sound signal separation. IWAENC2003, Kyoto,Japan.2003,9:15-18P
[138] S. Choi, A. Cichocki. Adaptive blind separation of speech signals: Cocktail party problem. International Conference on Speech Processing, 1997:617-622P
[139] Hyvarinen. Complexity pursuit: separating interesting components from time-series. Neural Computation. 2001,13 (4): 883-898P
[140] Long G Ling F, Proakis J G. Correction to "The LMS algorithms with delayed coefficient adaptation". IEEE Trans. On Acoustic, Speech, Signal Processing. 1992,40: 230-232P
[141] R. L. Zinser, G. Mirchandani, J. B. Evans. Some experimental and theoretical results using a new adaptive filter structure for noise cancellation in the presence of crosstalk. IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP, Tampa. 1985, 3:1253-1256P
[142] Mirchandani, G.; Gaus, R., Jr.; Bechtel, L.; Performance characteristics of a hardware implementation of the cross-talk resistant adaptive noise canceller.Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP'86. Apr 1986,11:93-96P
[143] G. Madhavan, H. D. Bruin. Crosstalk Resistant Adaptive Noise Cancellation", Annals of Biomedical Engineering, 1990,18(1):57-67P
[144] G. Mirchandani, R. L. Zinser, J. B. Evans, "A new Adaptive Noise Cancellation Scheme in the Presence of Crosstalk", IEEE Transaction on Circuits and System, 1992,39 (10):681-694P
[145] Vijay Parsa, Philip A. Parker, Robert N. Scott. Performance analysis of a crosstalk resistant adaptive noise canceller.IEEE Transcations on Circuits and Systems-Ⅱ:Analog and Digital Signal Processing,1996,43(7):473-482P
[146]Kuo,S.M.,Peng,W.M.Principle and applications of asymmetric crosstalkresistant adaptive noise canceller.Proc.IEEE workshop on Signal Processing System,October.1999:605-614P
[147]Qingning Zeng,Waleed H.Abdulla.Speech enhancement by multi-channel crosstalk resistant adaptive noise cancellation.IEEE International Conference on Acoustics,Speech and Signal Processing,2006.ICASSP 2006.2006,1:1-485-488P
[148]鲍雪山.被动目标DEMON检测方法研究及处理系统方案设计.哈尔滨工程大学硕士学位论文.2005.
[149]张翼鹏,何正耀.舰船辐射噪声建模及仿真研究.电声技术.2005,(12):52-55页
[150]李耀波,任志良,刘恩洋.一种鱼雷辐射噪声的线谱估计方法.指挥控制与仿真.2006,28(1):63-65页,70页
[151]王庆福,杜栓平.目标辐射噪声中线谱序列的提取方法.应用声学.2006,25(6):364-369页
[152]胡伟文,肖锋,苑秉成.目标辐射噪声线谱的特征建模与检测.海军工程大学学报.2006,18(6):45-48页
[153]张平华,王玲.基于自适应IIR陷波滤波器的窄带干扰抑制技术.现代雷达.2006,28(10):56-58页
[154]张世平,赵永平,张绍卿,李德胜.一种改进的自适应格型陷波滤波器.哈尔滨工业大学学报.2003,35(8):989-991页,995页
[155]Dennis R.Morgan,Charles Sanford.A control theory approach to the stability and transient analysis of the Filtered-X LMS adaptive notch filter.IEEE Trans.Signal Processing.1992,40(9):2341-2346P
[156]Lisa A.Sievers,Andreas H.von Flotow.Comparison and extensions of control methods for narrow-band disturbance rejection.IEEE Trans.Signal Processing.1992,40(10):2377-2389P
[157] Neil J. Bershad, Jose Carlos M. Bermudez. Sinusoidal interference rejection analysis of an LMS adaptive feedforward controller with a noisy periodic reference. 1992,46(5):1298-1312P
[158] John R.Glover. Adaptive noise canceling applied to sinusoidal interferences.IEEE Trans. Acoustics, Speech and Signal Processing, 1977,25(6): 484-491P
[159] Laszlo Sujbert, Gabor Peceli.Signal model based periodic noise controller design. Measurement. 1997,20(2):135-141P
[160] Marc Bodson, Jonathan S.Jensen, Scott C.Douglas. Active noise control for periodic disturbances. IEEE Trans. Control Systems Technology, 2001, 9(1):200-205P
[161] D.R.Morgan, J.Thi. A delayless subband adaptive filter. IEEE Trans. Signal Processing, 1995, 8: 1819-1830P
[162] James Thi, Dennis R.Morgan. Delayless subband active noise control.proceeding of IEEE, 1993.181-184P
[163] Jeong-Hyeon Yun, Young-Cheol Park, Dae-Hee Youn. An active noise control algorithm with on-line system identification based on delayless subband adaptive filter architecture. Proceeding of IEEE. 1997:1370-1373P
[164] Seon Joon Park, Jeong Hyeon Yun, Young Cheol Park, Dae Hee Youn. A delayless subband active noise control system for wideband noise control.IEEE Trans. Speech and Audio Processing. 2001,9(8):892-899P
[165] J. Poshtan, F. Taringoo, A. Nasiri, M. H. Kahaie. Multichannel active noise control algorithm using align matrix. Proceeding of IEEE. 2003: 435-438P
[166] Mariane R. Petraglia, Rogerio G. Alves, M. N. S. Swamy. A new open loop delayless subband adaptive filter structure. Proceeding of IEEE. 2002:1345-1348P
[167]N.Erd(o|¨)l,F.Basbug.Performance of wavelet transform based adaptive filters,in IEEE Int.Conf.Acoust.Speech Signal Processing,Apr.1993,3:500-503P
[168]F.Jiang,N.Ojiro,H.Ohmori,A.Sano.Adaptive active noise Control Schemes in Time-Domain and Transform-Domains.Proceeding of the 34~((th))Conference on Decision & Control,New Orleans,LA,Decemeber.1995,3:2165-2172P
[169]Nurgun Erdol,Filiz Basbug.Wavelet transform based adaptive filters:analvsis and new results.IEEE Transactions on Signal Processing,1996,44(9):2163-2171P
[170]Silnath Hosur,Ahmed H.Tewfik.Wavelet transform domain adaptive FIR filtering.IEEE Transactions on Signal Processing.1997,45(3):617-630P
[171]Samir Attallah.The wavelet transform-domain LMS algorithm:A more practical approach.IEEE Transactions on Circuits and Systems-Ⅱ:Analog and Digital Signal Processing.2000,47(3):209-213P
[172]Rodrigo Licio Ortolan,Ricardo Naoki Moil,Roberto R.Pereira,Jr.Cristina M.N.Cabral,José Carlos Pereira,Alberto Cliquet,Jr.Evaluation of adaptive/nonadaptive filtering and wavelet transform techniques for noise reduction in EMG mobile acquisition equipment.IEEE Transactions on Neural Systems and Rehabilitation Engineering.2003,11(1):60-69P
[173]刘湘黔,张霖.小波分析及其在控制中的应用:进展和展望.计算机自动测量与控制.1999,7(4):56-58页
[174]张子瑜,陈进,史习智.一种基于小波级数分解的LMS自适应除噪方法.振动工程学报.1999,12(1):73-77页
[175]万建,徐德民,贺昱曜.一种小波变换域的自适应扰动消除方法.电机与控制学报.2001,5(4):267:270页
[176]周元建,彭晗.小波变换域多路回波消除自适应滤波算法.湖南工程学院学报.2004,14(1):5-9页
[177]Wenhua Han,Peiwen Que.A modified wavelet transform domain adaptive FIR filtering algorithm for removing the SPN in the MFL data. Measurement.2006,39:621-627P
[178]刘金琨,刘涛.基于小波神经网络的自适应逆控制及其应用.系统工程与电子技术.2003,25(5):591-594页
[179]Mallat,S.A wavelet tour of signal processing,Academic Press.1998
[180]Snyder S D,Hansen C H.The effect of transfer function estimation error on the filtered-X LMS algorithm,IEEE Trans.On signal Processing,1994,42(4):950-953P
[181]S.J.Elliot,Signal Processing for Active Control.London,U.K.:Academic,2001.
[182]Long G,Ling F,Proakis J G.The LMS algorithms with delayed coefficient adaptation.IEEE Trans.On Acoustic,Speech,Signal Processing.1989,37:1397-1404P
[183]Eriksson L J.development of the filtered-U algorithm for active noise control.Journal of the acoustical society of America,89(1),1991:247-264P
[184]Van Overbeek M W R M.A method to identify the secondary path in active noise control systems.Proceedings of First Conference on Recent Advances in Active Control of Sound and Vibration.1991:742-743P
[185]Kuo S M,Vijayan D.A secondary path modeling technique for active noise control systems.IEEE Trans.On Speed and Audio Processing.1997,4(4),374-477P
[186]Morgan D R.A note on "a secondary path modeling technique for active noise control systems".IEEE Trans.On Speech and Audio Processing.7(4),1999:601-602P
[187]Muhammad Tahir Akhtar,Masahide Abe,Masayuki Kawamata.A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems.IEEE Transactions on Speech and Audio Processing.2006,14(2):720-726P
[188]Muhammad Tahir Akhtar,Masahide Abe,Masayuki Kawamata.A new structure for feedforward active noise control systems with improved online secondary path modeling.IEEE Transactions on Speech and Audio Processing. 2005,13(5):1082-1088P
[189] Sen M. Kuo, Dipa Vijayan. A secondary path modeling technique for active noise control systems. IEEE Transactions on Speech and Audio Processing.1997, 5(4):374-377P
[190] Ming Zhang, Hui Lan, Wee Ser. An improved secondary path modeling method for active noise control systems. IEEE Signal Processing Letters.2000, 7(4):73-75P
[191] D. Cornelissen, P. C. W. Sommen. New online secondary path estimation in a multipoint filtered-X algorithm for acoustic noise canceling. Proc.ProRISC 99, 10th Annual Workshop on Circuits, Systems and Signal Processing. Utrecht, Netherlands. 1999, 97-103P
[192] Hui Lan, Ming Zhang, Wee Ser. An active noise control system using online secondary path modeling with reduced auxiliary noise. IEEE Signal Processing Letters. 2002, 9(1):16-18
[193] R. H. Kwong, E.W. Johnston. A variable step size LMS algorithm. IEEE Trans. Signal Process. 1992. 40(7): 1633-1642P
[194] T. Aboulnasr, K. Mayyas. A robust variable step-size LMS-type algorithm:Analysis and simulations. IEEE Trans. Signal Process, 1997, 45(3):631-639P
[195] D. I. Pazaitis, A. G. Constantinides. A novel kurtosis driven variable step-size adaptive algorithm. IEEE Trans. Signal Process. 1999.47(3):864-872P
[196] W. P. Ang, F. Boroujeny. A new class of gradient adaptive stepsize LMS algorithms. IEEE Trans. Signal Process. 2001,49(4): 805-810P
[197] S. Koike. A class of adaptive step-size control algorithms for adaptive filters. IEEE Trans. Signal Process. 2002,50(6): 1315-1326P
[198] Tak Keung Yeung, Sze Fong Yau. Convergence analysis of multichannel ANC system using FXLMS algorithm with inexact secondary path model.Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).2003 IEEE International Conference. 2003,4:476-479P
[199]Orlando José Tobias,Rui Seara.Leaky-FXLMS algorithm:stochastic analysis for Gaussian data and secondary path modeling error.IEEE IEEE Transactions on speech and audio processing.2004 13(6):1217-1230
[200]Paulo A.C.Lopes,Moisés S.Piedade.-The behavior of the modified FX-LMS algorithm with secondary path modeling errors.IEEE Signal Processing Letters.2004,11(2):148:141P
[201]Sen M.Kuo,Dipa Vijayan.A secondary path modeling technique for active noise control systems.IEEE Transactions on Speech and Audio Processing.1997,4(4):374-377P
[202]Ming Zhang,Hui Lan,Wee Ser.An improved secondary path modeling method for active noise control systems.IEEE Signal Processing Letters.2000,7(4):73-74P
[203]Hui Lan,Ming Zhang,Wee Ser.An active noise control system using online secondary path modeling with reduced auxiliary noise.IEEE Signal Processing Letters.2002,9(1):16-18P
[204]Mitra S.K.,Digital Signal Processing A Computer Based Approach,First Edition,McGraw-Hill,New York,1998:462-468P
[205]Jackson L.B.,Digital Filters and Signal Processing,Third Edition,Kluwer Academic Publishers,Boston,1996:301-307P
[206]王宗锋,张奇志.基于同步方程方法的有源噪声控制.电声技术.2006,9:56-59页
[2]陈克安.有源噪声控制.北京:国防工业出版社,2003:1-9页
[3]Lueg P.Process of silencing sound oscillations,German patent DRP No.644408,1933
[4]Lueg P.Process of silencing sound oscillations,US patent No.2043416,1936
[5]Widrow B,Glover J R,McCool J M.Adaptive noise cancellation:principle and applications,Proceeding of IEEE.1975,63(12):1692-1716P
[6]Burgress J.C.Active adaptive sound control in a duct:a computer simulation.Journal of the Acoustical Society of America.1981:70(3),714-726P
[7]S.J.Elliott,I.M.Stothers,P.A.Nelson,A.M.McDonald,D.C.Quinn,T.Saunders.The active control of engine noise inside cars,Proc.Inter-noise.1988:987-990P
[8]A.M.McDonald,S.J.Elliott,M.A.Stokes.Active noise and vibration control within the automobile,Proc.Int.Symp.Active control of Sound Vibration.1991:147-156P
[9]Y.Kurata,N.Koike.Adaptive active attenuation of interior car noise,Proc.Int.Symp.Active control of Sound Vibration.1991:297-302P
[10]C.F.Ross.the control of noise inside passenger vehicles,Proc.Recent Advances in Active control of Sound Vibration.1991:671-681P
[11]S.M.Kuo,B.M.Finn.A general multi-channel filtered LMS algorithm for 3-D active noise control systems.Proc.2nd Int.Conf.Recent development in Air- and Structure- Borne Sound Vib.1992:345-352P
[12]M.A.Simpson,T.M.Luong,M.A.Swinbanks,M.A.Russell,H.G.Leventhall,Full scale demonstration tests of cabin noise reduction using active nose control.Proc.Inter-noise.1989:459-462P
[13]C.M.Dorling,G.P.Eatwell,S.M.Hutchins,C.F.Ross,S.G.C.Sutcliffe.A demonstration of active noise reduction in an aircraft cabin.J.Sound Vibration.1989:128(2):358-360P
[14]S.J.Elliott,P.A.Nelson,I.M.Stotheers,C.C.Boucher.In-flight experiments on the active control of propeller-induced cabin noise.J.Sound Vibration.1990,140(2):219-238P
[15]J.-D.WU,M.R.BAI.Application of feedforward adaptive active-noise control for reducing blade passing noise in centrifugal fans.Journal of Sound and Vibration.2001,239(5):1051-1062P
[16]JamesP.Carneal,ChrisR.Fuller.An analytical and experimental investigation of active structural acoustic control of noise transmission through double panel systems.Journal of Sound and Vibration.2004,272:749-771P
[17]Yuan It.Guan,Teik C.Lim,W.Steve Shepard,Jr.Experimental study on active vibration control of a gearbox system.Journal of Sound and Vibration.2005,282:713-733 P
[18]Desheng Li.Active control of aircraft cabin noise and vibration using a physical model:[PhD dissertation].Université Laval,Québec Canada.2002,12.
[19]美国在C-130H飞机的座舱中安装ANC主动噪声控制系统.现代兵器.2004,(5):46页
[20]LAU,Siu Kit.Active control of sound transmission into enclosure through a panel:[PhD dissertation].Hong Kong Polytechnic University.2002,12.
[21]Theeraphong Chanpheng,Hitoshi Yamada,Toshio Miyata,Hiroshi Katsuchi.Application of radiation modes to the problem of low-frequency noise from a highway bridge.Applied Acoustics,2004,65:109-123P
[22]陈克安,马远良.自适应有源噪声控制--原理、算法及实现.西安:西北工业大学出版社,1993:280页
[23]D.H.Crawford and R.W.Stewart,E.Toma.A novel adaptive IIR filter for active noise control. Proceeding of the IEEE, 1996:1629-1632P
[24] Scott D.Snyder. Active control using IIR filters- a second look. Proceeding of the IEEE, 1994:241-244P
[25] Jong Boo Kim, Tae Pyo Lee, Kook Hyun Yim. Feedforward IIR active noise control using genetic algorithm. Proceeding of the IEEE, 1999:436-441P
[26] Carlos Mosquera, Jose A, Gomez and Fernando Perez-Gonzalez. Filtered error adaptive algorithms and their application to active noise control.Proceeding of the IEEE, 1998:1701-1704P
[27] Kook Hyun Yim, Jong Boo Kim, Tae Pyo Lee, Doo Soo Ahn. Genetic adaptive IIR filtering algorithm for active noise control. Proceedings of IEEE International Fuzzy Systems Conference, 1999:1723-1728P
[28] Akhtar, M.T.; Abe, M.; Kawamata, M.; A new method for active noise control systems with online acoustic-feedback-path modeling. IEEE International Conference on Engineering of Intelligent Systems 22-23 April 2006:1-6P
[29] Martin Bouchard. Numerically stable fast convergence least-squares algorithms for multichannel active sound cancellation systems and sound deconvolution systems. Signal Processing. 2002:721-736P
[30] Martin Bouchard, Stephan Quednau. Multichannel recursive-least-squares algorithms and fast-transversal-filter algorithm for active noise control and sound reproduction systems. IEEE Trans. Acoustics, Speech and Signal Processing,2000,8(5): 606-618P
[31] Young C. Park, Scott D. Sommerfeldt. A fast adaptive noise control algorithm based on the lattice structure. Applied Acoustics. 1996,47:1-25P
[32] Kensaku Fujii, Juro Ohga. Method to update the coefficients of the secondary path filter under active noise control. Signal Processing.2001,81:381-387P
[33] X.Qiu, C.H.Hansen. An algorithm for active control of transformer noise with on-line cancellation path modelling based on the perturbation method. Journal of Sound and Vibration. 2001,240(4):647-665P
[34] Alberto Gonzalez, Jose J.Lopez. Time domain recursive deconvolution in sound reproduction. IEEE, 2000:833-835P
[35] H.-S. Kim, Y.Park. Delayed-X LMS algorithm: an efficient ANC algorithm utilizing robustness of cancellation path model. Journal of Sound and Vibration. 1998, 212(5):875-887P
[36] D.C.Swanson, S.M.Hirsch, K.M.Reichard, J.Tichy. Development of a frequency-domain filtered-x intensity ANC algorithm. Applied Acoustics,1999:39-49P
[37] Cheng-Yuan Chang and Kuo-Kai Shyu. A self-tuning fuzzy filtered-U algorithm with the application of active noise control. The 27th Annual Conference of the IEEE Industrial Electronics Society. 2001:474-478P
[38] Sven Johansson, Sven Nordebo, Ingvar Claesson. Convergence analysis of a twin-reference complex least-mean-squares algorithm. IEEE Trans. on Speech and Audio Processing.2002:213-221P
[39] A. Kuo Wang, Wei Ren. Convergence analysis of the filtered-U algorithm for active noise control. Signal Processing. 1999.73:255-266P
[40] Martin Bouchard. Inverse structure for active noise control and combined active noise control/sound reproduction systems. IEEE Trans. Speech and Audio Processing. 2001,9(2):141-151P
[41] Masato Miyoshi, Yutaka Kaneda. Inverse filtering of room acoustics. IEEE Trans. on Acoustics, Speech, and Signal Processing. 1988, 36(2):145-152P
[42] Martin bouchard. New recursive-least-squares algorithms for nonlinear active control of sound and vibration using neural networks. IEEE Trans. on Neural Networks.2001,12(1):135-147P
[43] Li Tan, Jean Jiang. Adaptive volterra filters for active control of nonlinear noise processes. IEEE Trans. on Signal Processing.2001,49(8): 1667-1676P
[44] Debi Prasad Das, Ganapati Panda. Active mitigation of nonlinear noise processes using a novel filtered-s LMS algorithm. IEEE Trans. On Speech and Audio Processing. 2004, 12(3):313-322P
[45]Ya-Li Zhou,Qi-Zhi Zhang,Xiao-Dong Li,Woon-Seng Gao.Analysis and DSP implementation of an ANC system using a filtered-error neural network.Journal of Sound and Vibration.2005,285:1-25P
[46]K.Mayyas,T.Aboulnasr.A fast exact weighted subband adaptive algorithm and its application to mono and stereo acoustic echo cancellation.Journal of the Franklin Institute.2005,342:235-253P
[47]Bernhard H.Nitsch.A frequency-selective stepfactor control for an adaptive filter algorithm working in the frequency domain.Signal Processing.2000,80:1733-1745P
[48]孙利峰,陈克安,谢达.多通道有源控制算法硬件实现及影响因素研究.电声技术.2007,31(2):63-66页
[49]陈克安,陈国跃,李双,潘浩然.分布式位移传感下的有源声学结构误差传感策略.声学学报.2007,32(1):42-48页
[50]李双,陈克安.有源声学结构次级声源的布放规律研究.机械科学与技术.2006,2(11):1351-1357页
[51]陈克安,尹雪飞.应用于多通道有源控制的自适应组合逆算法.信号处理.2006,22(3):366-369页
[52]张玉麟.小波自适应控制系统及其在噪声主动控制中的应用研究.重庆大学博士学位论文.2002:4页
[53]张玉麟,陈伟民,黄尚廉.噪声主动控制中的自适应算法和传函识别研究.中国机械工程.2002,13(1):46-49页
[54]张玉麟,陈伟民,黄尚廉,小波变换自适应滤波器及在噪声主动控制中的应用.控制与决策.2002,17(1):107-110页
[55]孙旭,陈端石.基于无限脉冲响应滤波器的自适应滤波E型有源噪声控制算法.声学学报.2003,28(2):171-176页
[56]孙旭,陈端石.次级通道模型误差下滤波X型最小均方差算法性能的分析.声学学报.2003,28(1):73-78页
[57]于华民,朱海潮,施引.管道复合主动噪声控制系统及其实现.振动、测试与诊断.2004,24(2):153-156页
[58]王登峰,刘学广,刘宗巍,梁杰.基于发动机转速的车内有源控制策略和 自适应算法.公路交通科技.2004,21(10):126-129页
[59]常振臣,王登峰.车內噪声控制技术研究现状及展望.吉林大学学报(工学版).2002,32(4):86-90页
[60]常振臣,王登峰.车内噪声主动控制系统设计与实验研究.公路交通科技.2003,20(6):150-153页
[61]LI Keqiang,YANG Diange,ZHENG Sifa,LIAN Xiaomin,Tanaka Takeharu.Active Noise Control for Vehicle Exhaust Noise Reduction.清华大学学报(自然科学英文版).2003,8(5):577-581页
[62]吴亚锋,黎中伟,任辉.应用于主动噪声控制的实时DSP系统.振动与冲击.2002,21(2):91-93页
[63]吴亚锋,任辉,李江红.螺桨飞机舱内噪声的主动控制.声学技术.2001,20(1):29-31页
[64]吴亚锋.三维闭空间主动噪声控制的实验研究.振动与冲击.2001,20(4):33-35页
[65]任辉,黎中伟.主动噪声控制声学通道的实验辨识.应用声学.1997,16(3):36-40页
[66]黎中伟代杏珍.螺浆飞机舱内主动噪声控制地面实验.西北工业大学学报.1996,14(4):651-653页
[67]胡啸,涂有.超机动车车室内复合主动噪声控制系统的设计.噪声与振动控制.2001,21(1):8-12页
[68]李传光,姜丽飞,李长青.RB网络在履带车辆舱室内有源降噪的实验研究.北京理工大学学报.2004,24(4):297-299页
[69]李传光,车星峰,韩秀苓.局部空间自适应有源降噪系统的实验研究.北京理工大学学报.2001,21(4):495-497页
[70]王杰.互耦多通道自适应有源噪声抵消技术研究.哈尔滨工程大学博士学位论文.2004:4页
[71]王杰,徐新盛,吴英姿.一种采用脉冲串的自适应有源干扰抵消器.应用声学.2004,23(6):45-50页
[72]王杰,徐新盛,刘清宇,吴英姿.一种用于宽带自噪声有源抵消的无延时子带多通道系统.噪声与振动控制.2004,24(4):5-7页,25页
[73]王杰,徐新盛,吴英姿.自噪声有源抵消器性能分析.海洋技术.2004,23(3):26-29页,33页
[74]张奇志,贾永乐.噪声有源稳定自适应控制.振动工程学报.2002,15(1):86-89页
[75]尹建民,周雅莉,张奇志,关碧华.有源噪声控制的一种变换域算法.应用声学.2004,23(3):33-39页
[76]张奇志,贾永乐.噪声有源控制的递归神经网络方法.控制与决策.2001,16(3):368-370页
[77]张志涛,张奇志.无模型技术在有源噪声控制中的应用.电声技术.2004,10:51-53页
[78]熊斌,张奇志,周雅莉,吕小明.内模型神经网络在有源噪声控制中的应用.电声技术.2005,11:58-60页
[79]朱晓健,韩彦民,张懿时,刘宝,徐琳琳.智能调频消声器的设计和实现.噪声与振动控制.2006,26(5):85-87页
[80]关碧华,周雅莉.噪声有源控制的模糊神经网络方法.北京机械工业学院学报.2002,17(3):11-14页
[81]李径定,罗永革.汽车车内结构噪声新型控制方法实验研究.汽车工程.2001,23(4):262-265页
[82]张菊香,邱阳.基于自调整量化因子模糊控制器的有源噪声控制.噪声与振动控制.2002,22(6):13-15页
[83]Simon Haykin.Adaptive filter theory.Fourth Edition.Beijing:Publishing House of Electronics Industry,2002:94-128P
[84]Widrow B,Stearns S D.Adaptive signal processing,Prentice-Hall,Englewood Cliffs,NJ,1985
[85]B.Widrow,E.Walach.自适应逆控制.刘树荣,韩崇昭译.西安:西安交通大学出版社,2000:52-59页
[86]Min-Chun Pan;Ji-Yao Liu;Active shock noise cancellation with variable step-size algorithms.Information Acquisition,2005 IEEE International Conference on 27 June-3 July 2005:198-203P
[87]Yue Wang;Chun Zhang;Zhihua Wang.A new variable step size LMS algorithm with application to active noise control.Acoustics,Speech,and Signal Processing,2003.Proceedings.(ICASSP '03).2003 IEEE International Conference.2003,5:573-575P
[88]Say-Wei Foo;Senthilkumar,T.N.;Averty,C.;Active noise cancellation headset.Circuits and Systems,2005.ISCAS 2005.IEEE International Symposium,23-26 May.2005,1:268-271P
[89]沙家正,孙广荣,曹水轩,吴启学.有源消声的机理研究.声学学报.1983,8(2):93-99页
[90]田静.关于单极子次级声源管道降噪能量机制的理论分析.声学学报.1992,17(5):369-374页
[91]Synder S D,Hansen C H.Active noise control in duct:Some physical insights.Journal of the Acoustical of America.1989,86:184-194P
[92]Elliott S J,Nelson P A,Johnson M E.Power output minimization and power absorption in the active control of sound.Journal of the Acoustical Society of America.1993,94:185-195P
[93]沙正明,沙家正,单扬声器的管道有源消声器.声学学报.1987,15(3):343-348页
[94]Warnaka G E,Poole L A,Tichy J.Active acoustic attenuators,U.S.Patent 4473906,1984
[95]Eriksson L J.Development of the filtered-U algorithm for active noise control,Journal of the Acoustical Society of America.1991,89(1):257-265P
[96]Burgress J C.Active adaptive sound control in a duct:a computer simulation,Journal of the Acoustical Society of America.1981,70(3):715-726P
[97]Bjarmason E.Analysis of the filtered-X LMS algorithm,IEEE Trans.On Speech and Audio Processing.1995,3:504-514P
[98]Feintuch P L,Bershad N J,Lo A K.A frequency domain model for "filtered" LMS algorithms - stability analysis,design,and elimination of the training mode,IEEE Trans.On Signal Processing.1993,41(4):1518-1531P
[99]陈克安,马远良.自适应宽带有源消声.声学学报.1994,19(2):101-109页
[100]Radoslav Bortel,Pavel Sovka.EEG-EMG coherence enhancement.Signal Processing.2006,86:1737-1741P
[101]Sen M.Kuo,Dennis R.Morgan.Active noise control:a tutorial review.Proceedings of the IEEE.1999,87(6):943-973P
[102]Eriksson L J,Allie M C.Allie.Use of random noise for on-line transducer modeling in an adaptive active attenuation system.Journal of the Acoustical Society of America.1989,85:797-802P
[103]Rufus Fraanje,Michel Verhaegen,Nick Doelman.Convergence analysis of the Filtered-U LMS algorithm for active noise control in case perfect cancellation is not possible.Signal Processing.2003,83:1239-1244P
[104]S.M.Kuo,D.R.Morgan.Active Noise Control Systems:Algorithm and DSP Implementations.New York:Wiley.1996.
[105]M.Ayala Botto,J.M.C.Sousa da Costa,J.M.G.Sá.Intelligent active noise control applied to a laboratory railway coach model.Control Engineering Practice.2004,13:473-484P
[106]Jing Yuan.A hybrid active noise controller for finite ducts.Applied Acoustics.2004,64:44-47P
[107]Jun-il Sohn,Minho Lee.Selective attention system using new active noise controller.Neurocomputing.2000,31:197-204P
[108]刘伯胜,雷加煜.水声学原理.哈尔滨:哈尔滨工程大学出版社,1997:159-183页,213-236页
[109]沙家正.管道有源消声器.声学学报.1982,7(2):137-147页
[110]Swinbanks M A.The active control of sound propagation in long ducts.Journal of Sound and Vibration.1973:411-436P
[111]谷萩隆嗣.语音与图像的数字信号处理.朱虹译.北京:科学出版社,2003:11-17页
[112]Itoh Y.,Tajima K.,Kuwabara N..Measurement of subjective communication quality for optical mobile communication systems by using mean opinion score.Personal,Indoor and Mobile Radio Communications,2000.PIMRC 2000.The 11th IEEE International Symposium on,2000,2:1330-1334P
[113]Andres Buzo,Federico Kuhlmann,Carlos Rivera.Rate-distortion bounds for quotient-based distortions with application to Itakura-Saito distortion measures.IEEE transactions on information theory.1986,32(2):141-147P
[114]Hermansky H.Perceptual Linear Predictive(PLP) Analysis of Speech.The Journal of the Acoustical Society of America.1990,87(4):1738-1752P
[115]易克初,田斌,付强.语音信号处理.北京:国防工业出版社,2000:331-339页,135-148页
[116]Wonho Yang,Benbouchta,M.,Yantorno,R..Performance of the modified Bark spectraldistortion as an objective speech quality measure.Acoustics,Speech,and Signal Processing,1998.ICASSP '98.Proceedings of the 1998IEEE International Conference on,Seattle,WA,USA.1998,1:541-544P
[117]Wonho Yang,Yantorno R.Improvement of MBSD by scaling noise masking threshold and correlation analysis with MOS difference instead of MOS.Acoustics,Speech,and Signal Processing,1999.ICASSP '99.Proceedings of the 1999 IEEE International Conference on,Phoenix,AZ,USA,1999,2:673-676P
[118]P.Comon.Independent component analysis-a new concept.Signal Processing.1994,36:287-314P
[119]Delfosse,N.,Loubaton,P.Adaptive blind separation of independent sources:A deflation approach.Signal Processing.1995,45:59-83P
[120]Ye Jimin,Zhang Xianda,Zhu Xiaolong.Blind source separation with unknown and dynamicall changing number of source Signals.Science in China Series F:Information Sciences.2006,49(5):627-638P
[121]徐尚志,苏勇,叶中付.欠定条件下的盲分离算法.数据采集与处理,2006,21(2):128-132页
[122]M.Joho,H.Mathis,R.H.Lambert,Overdetermined blind source separation:using more sensors than source signals in a noisy mixture,Proceedings of International Conference on Independent Component Analysis and Blind Signal Separation(ICA).Helsinki,Finland,June 19-22,2000:81-86P
[123]J.S(a|¨)rel(a|¨),H.Valpola.Denoising source separation.Journal of Machine Learning Research.2005,6:233-272P
[124]梅铁民.盲源信号分离时域与频域算法研究.大连理工大学博士学位论文.2005:28-134页
[125]C.Jutten,J.Karhunen.Advances in blind source separation(BSS) and independent component analysis(ICA) for nonlinear mixtures.Int.J.of Neural Systems.2004,14(5):267-292,2004P
[126]Su Yong,Xu Shangzhi,Ye Zhongfu.Blind channel identication of nonlinear folding mixing model.Journal of Systems Engineering and Electronics.2006,17(3):509-512P
[127]Aapo Hyv(a|¨)inen,Erkki Oja,Independent component analysis:algorithms and applications.Neural Networks.2000,13(4-5):411-430P
[128]Hyv(a|¨)inen,E.Oja,A fast fixed-point algorithm for independent component analysis.Neural Computation.1997,9:1483-1492P
[129]Bell A.J.,Sejnowski T.J.Edges are the independent components of natural scenes.Advances in Neural Information Processing Systems 9.MIT press.1996.
[130]Lee T W Bell A J,Lambert Blind separation ofdelayed and convolved sources,in Advances in Neural Information Processing Systems 9.Combridge,MA:MIT Press,1997:758-764P
[131]Ikeda S,Murata N.A method of ICA in time-frequency domain,in Int.Conf.ICA and Signal Separation Aussois,France.1999:365-371P
[132]Bell A.J.,Sejnowsld T.J.An information maximization approach to blind separation and blind deconvolution.Neural Computation,1995,7(6):1129-1159P
[133]Smaragdis P.Blind separation of convolved mixtures in the frequency domain.Neurocomputing.1998,22(6):21-34P
[134]Parra L,Spence C.Convolutive blind separation of non-stationary sources.IEEE Trans.Speech Audio Processing.2000,8(3):320-327P
[135]Asano E Ikeda S,Ogawa M,Asoh H,Kitawaki N.Combined approach of array processing and independence component analysis for blind separation of acoustic signals. IEEE trans. Speech, Audio Processing.2003,11(5):204-215P
[136] Murata N, Ikeda S, Ziehe A. An approach to blind source separation based on temporal structure of speech signals. Neurocomput. 2001,41(2):1-24P
[137] Matsuoka K. Independent component analysis and its applications to sound signal separation. IWAENC2003, Kyoto,Japan.2003,9:15-18P
[138] S. Choi, A. Cichocki. Adaptive blind separation of speech signals: Cocktail party problem. International Conference on Speech Processing, 1997:617-622P
[139] Hyvarinen. Complexity pursuit: separating interesting components from time-series. Neural Computation. 2001,13 (4): 883-898P
[140] Long G Ling F, Proakis J G. Correction to "The LMS algorithms with delayed coefficient adaptation". IEEE Trans. On Acoustic, Speech, Signal Processing. 1992,40: 230-232P
[141] R. L. Zinser, G. Mirchandani, J. B. Evans. Some experimental and theoretical results using a new adaptive filter structure for noise cancellation in the presence of crosstalk. IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP, Tampa. 1985, 3:1253-1256P
[142] Mirchandani, G.; Gaus, R., Jr.; Bechtel, L.; Performance characteristics of a hardware implementation of the cross-talk resistant adaptive noise canceller.Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP'86. Apr 1986,11:93-96P
[143] G. Madhavan, H. D. Bruin. Crosstalk Resistant Adaptive Noise Cancellation", Annals of Biomedical Engineering, 1990,18(1):57-67P
[144] G. Mirchandani, R. L. Zinser, J. B. Evans, "A new Adaptive Noise Cancellation Scheme in the Presence of Crosstalk", IEEE Transaction on Circuits and System, 1992,39 (10):681-694P
[145] Vijay Parsa, Philip A. Parker, Robert N. Scott. Performance analysis of a crosstalk resistant adaptive noise canceller.IEEE Transcations on Circuits and Systems-Ⅱ:Analog and Digital Signal Processing,1996,43(7):473-482P
[146]Kuo,S.M.,Peng,W.M.Principle and applications of asymmetric crosstalkresistant adaptive noise canceller.Proc.IEEE workshop on Signal Processing System,October.1999:605-614P
[147]Qingning Zeng,Waleed H.Abdulla.Speech enhancement by multi-channel crosstalk resistant adaptive noise cancellation.IEEE International Conference on Acoustics,Speech and Signal Processing,2006.ICASSP 2006.2006,1:1-485-488P
[148]鲍雪山.被动目标DEMON检测方法研究及处理系统方案设计.哈尔滨工程大学硕士学位论文.2005.
[149]张翼鹏,何正耀.舰船辐射噪声建模及仿真研究.电声技术.2005,(12):52-55页
[150]李耀波,任志良,刘恩洋.一种鱼雷辐射噪声的线谱估计方法.指挥控制与仿真.2006,28(1):63-65页,70页
[151]王庆福,杜栓平.目标辐射噪声中线谱序列的提取方法.应用声学.2006,25(6):364-369页
[152]胡伟文,肖锋,苑秉成.目标辐射噪声线谱的特征建模与检测.海军工程大学学报.2006,18(6):45-48页
[153]张平华,王玲.基于自适应IIR陷波滤波器的窄带干扰抑制技术.现代雷达.2006,28(10):56-58页
[154]张世平,赵永平,张绍卿,李德胜.一种改进的自适应格型陷波滤波器.哈尔滨工业大学学报.2003,35(8):989-991页,995页
[155]Dennis R.Morgan,Charles Sanford.A control theory approach to the stability and transient analysis of the Filtered-X LMS adaptive notch filter.IEEE Trans.Signal Processing.1992,40(9):2341-2346P
[156]Lisa A.Sievers,Andreas H.von Flotow.Comparison and extensions of control methods for narrow-band disturbance rejection.IEEE Trans.Signal Processing.1992,40(10):2377-2389P
[157] Neil J. Bershad, Jose Carlos M. Bermudez. Sinusoidal interference rejection analysis of an LMS adaptive feedforward controller with a noisy periodic reference. 1992,46(5):1298-1312P
[158] John R.Glover. Adaptive noise canceling applied to sinusoidal interferences.IEEE Trans. Acoustics, Speech and Signal Processing, 1977,25(6): 484-491P
[159] Laszlo Sujbert, Gabor Peceli.Signal model based periodic noise controller design. Measurement. 1997,20(2):135-141P
[160] Marc Bodson, Jonathan S.Jensen, Scott C.Douglas. Active noise control for periodic disturbances. IEEE Trans. Control Systems Technology, 2001, 9(1):200-205P
[161] D.R.Morgan, J.Thi. A delayless subband adaptive filter. IEEE Trans. Signal Processing, 1995, 8: 1819-1830P
[162] James Thi, Dennis R.Morgan. Delayless subband active noise control.proceeding of IEEE, 1993.181-184P
[163] Jeong-Hyeon Yun, Young-Cheol Park, Dae-Hee Youn. An active noise control algorithm with on-line system identification based on delayless subband adaptive filter architecture. Proceeding of IEEE. 1997:1370-1373P
[164] Seon Joon Park, Jeong Hyeon Yun, Young Cheol Park, Dae Hee Youn. A delayless subband active noise control system for wideband noise control.IEEE Trans. Speech and Audio Processing. 2001,9(8):892-899P
[165] J. Poshtan, F. Taringoo, A. Nasiri, M. H. Kahaie. Multichannel active noise control algorithm using align matrix. Proceeding of IEEE. 2003: 435-438P
[166] Mariane R. Petraglia, Rogerio G. Alves, M. N. S. Swamy. A new open loop delayless subband adaptive filter structure. Proceeding of IEEE. 2002:1345-1348P
[167]N.Erd(o|¨)l,F.Basbug.Performance of wavelet transform based adaptive filters,in IEEE Int.Conf.Acoust.Speech Signal Processing,Apr.1993,3:500-503P
[168]F.Jiang,N.Ojiro,H.Ohmori,A.Sano.Adaptive active noise Control Schemes in Time-Domain and Transform-Domains.Proceeding of the 34~((th))Conference on Decision & Control,New Orleans,LA,Decemeber.1995,3:2165-2172P
[169]Nurgun Erdol,Filiz Basbug.Wavelet transform based adaptive filters:analvsis and new results.IEEE Transactions on Signal Processing,1996,44(9):2163-2171P
[170]Silnath Hosur,Ahmed H.Tewfik.Wavelet transform domain adaptive FIR filtering.IEEE Transactions on Signal Processing.1997,45(3):617-630P
[171]Samir Attallah.The wavelet transform-domain LMS algorithm:A more practical approach.IEEE Transactions on Circuits and Systems-Ⅱ:Analog and Digital Signal Processing.2000,47(3):209-213P
[172]Rodrigo Licio Ortolan,Ricardo Naoki Moil,Roberto R.Pereira,Jr.Cristina M.N.Cabral,José Carlos Pereira,Alberto Cliquet,Jr.Evaluation of adaptive/nonadaptive filtering and wavelet transform techniques for noise reduction in EMG mobile acquisition equipment.IEEE Transactions on Neural Systems and Rehabilitation Engineering.2003,11(1):60-69P
[173]刘湘黔,张霖.小波分析及其在控制中的应用:进展和展望.计算机自动测量与控制.1999,7(4):56-58页
[174]张子瑜,陈进,史习智.一种基于小波级数分解的LMS自适应除噪方法.振动工程学报.1999,12(1):73-77页
[175]万建,徐德民,贺昱曜.一种小波变换域的自适应扰动消除方法.电机与控制学报.2001,5(4):267:270页
[176]周元建,彭晗.小波变换域多路回波消除自适应滤波算法.湖南工程学院学报.2004,14(1):5-9页
[177]Wenhua Han,Peiwen Que.A modified wavelet transform domain adaptive FIR filtering algorithm for removing the SPN in the MFL data. Measurement.2006,39:621-627P
[178]刘金琨,刘涛.基于小波神经网络的自适应逆控制及其应用.系统工程与电子技术.2003,25(5):591-594页
[179]Mallat,S.A wavelet tour of signal processing,Academic Press.1998
[180]Snyder S D,Hansen C H.The effect of transfer function estimation error on the filtered-X LMS algorithm,IEEE Trans.On signal Processing,1994,42(4):950-953P
[181]S.J.Elliot,Signal Processing for Active Control.London,U.K.:Academic,2001.
[182]Long G,Ling F,Proakis J G.The LMS algorithms with delayed coefficient adaptation.IEEE Trans.On Acoustic,Speech,Signal Processing.1989,37:1397-1404P
[183]Eriksson L J.development of the filtered-U algorithm for active noise control.Journal of the acoustical society of America,89(1),1991:247-264P
[184]Van Overbeek M W R M.A method to identify the secondary path in active noise control systems.Proceedings of First Conference on Recent Advances in Active Control of Sound and Vibration.1991:742-743P
[185]Kuo S M,Vijayan D.A secondary path modeling technique for active noise control systems.IEEE Trans.On Speed and Audio Processing.1997,4(4),374-477P
[186]Morgan D R.A note on "a secondary path modeling technique for active noise control systems".IEEE Trans.On Speech and Audio Processing.7(4),1999:601-602P
[187]Muhammad Tahir Akhtar,Masahide Abe,Masayuki Kawamata.A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems.IEEE Transactions on Speech and Audio Processing.2006,14(2):720-726P
[188]Muhammad Tahir Akhtar,Masahide Abe,Masayuki Kawamata.A new structure for feedforward active noise control systems with improved online secondary path modeling.IEEE Transactions on Speech and Audio Processing. 2005,13(5):1082-1088P
[189] Sen M. Kuo, Dipa Vijayan. A secondary path modeling technique for active noise control systems. IEEE Transactions on Speech and Audio Processing.1997, 5(4):374-377P
[190] Ming Zhang, Hui Lan, Wee Ser. An improved secondary path modeling method for active noise control systems. IEEE Signal Processing Letters.2000, 7(4):73-75P
[191] D. Cornelissen, P. C. W. Sommen. New online secondary path estimation in a multipoint filtered-X algorithm for acoustic noise canceling. Proc.ProRISC 99, 10th Annual Workshop on Circuits, Systems and Signal Processing. Utrecht, Netherlands. 1999, 97-103P
[192] Hui Lan, Ming Zhang, Wee Ser. An active noise control system using online secondary path modeling with reduced auxiliary noise. IEEE Signal Processing Letters. 2002, 9(1):16-18
[193] R. H. Kwong, E.W. Johnston. A variable step size LMS algorithm. IEEE Trans. Signal Process. 1992. 40(7): 1633-1642P
[194] T. Aboulnasr, K. Mayyas. A robust variable step-size LMS-type algorithm:Analysis and simulations. IEEE Trans. Signal Process, 1997, 45(3):631-639P
[195] D. I. Pazaitis, A. G. Constantinides. A novel kurtosis driven variable step-size adaptive algorithm. IEEE Trans. Signal Process. 1999.47(3):864-872P
[196] W. P. Ang, F. Boroujeny. A new class of gradient adaptive stepsize LMS algorithms. IEEE Trans. Signal Process. 2001,49(4): 805-810P
[197] S. Koike. A class of adaptive step-size control algorithms for adaptive filters. IEEE Trans. Signal Process. 2002,50(6): 1315-1326P
[198] Tak Keung Yeung, Sze Fong Yau. Convergence analysis of multichannel ANC system using FXLMS algorithm with inexact secondary path model.Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).2003 IEEE International Conference. 2003,4:476-479P
[199]Orlando José Tobias,Rui Seara.Leaky-FXLMS algorithm:stochastic analysis for Gaussian data and secondary path modeling error.IEEE IEEE Transactions on speech and audio processing.2004 13(6):1217-1230
[200]Paulo A.C.Lopes,Moisés S.Piedade.-The behavior of the modified FX-LMS algorithm with secondary path modeling errors.IEEE Signal Processing Letters.2004,11(2):148:141P
[201]Sen M.Kuo,Dipa Vijayan.A secondary path modeling technique for active noise control systems.IEEE Transactions on Speech and Audio Processing.1997,4(4):374-377P
[202]Ming Zhang,Hui Lan,Wee Ser.An improved secondary path modeling method for active noise control systems.IEEE Signal Processing Letters.2000,7(4):73-74P
[203]Hui Lan,Ming Zhang,Wee Ser.An active noise control system using online secondary path modeling with reduced auxiliary noise.IEEE Signal Processing Letters.2002,9(1):16-18P
[204]Mitra S.K.,Digital Signal Processing A Computer Based Approach,First Edition,McGraw-Hill,New York,1998:462-468P
[205]Jackson L.B.,Digital Filters and Signal Processing,Third Edition,Kluwer Academic Publishers,Boston,1996:301-307P
[206]王宗锋,张奇志.基于同步方程方法的有源噪声控制.电声技术.2006,9:56-59页